Regression Test: Price Checks For Promoted Transactions

Hey everyone! Let's dive into creating a robust regression test for a crucial aspect of our transaction processing: price checks for promoted transactions. This test aims to ensure that once a transaction's price is validated, it remains consistent throughout its lifecycle, even after being promoted and included in a block. We'll be focusing on a specific scenario outlined in a previous pull request. Basically, we're building a test that will trip a fail if a transaction's price is checked after it's included.

Understanding the Core Problem: Price Consistency

So, what's the big deal about price consistency, you ask? Well, in the world of blockchain, especially when dealing with promoted transactions, ensuring the price of a transaction remains stable is super important. When you promote a transaction, it means you're bumping up its priority, often by paying a higher fee, to get it included in a block faster. If the price of that transaction could change after it's been promoted and validated, chaos would ensue. Think about it: a transaction might be initially validated at a certain price, but if the price fluctuates drastically after promotion, it could lead to issues like unexpected fees or even failed transactions. This is where our test comes in handy to prevent price manipulation.

Imagine a situation where a malicious actor tries to game the system. They could submit a transaction at a low price, get it validated, promote it, and then somehow try to alter the price after validation. Our regression test is designed to catch these kinds of shenanigans. By verifying that the price checks remain consistent throughout the transaction's journey, we maintain the integrity and predictability of the system. In short, this test makes sure the price you see is the price you pay. This helps maintain the financial predictability and fairness that everyone expects from a solid blockchain.

Setting the Stage: Lowering the EMA Interval

To make this test effective, we're going to use the Exponential Moving Average (EMA) interval. The EMA is a calculation that helps smooth out price fluctuations over time. For our test, we'll configure the EMA interval to two blocks. This configuration means that the EMA will recalculate the price every two blocks. To start, include a transaction as a 'JUST submit' for block 1, which means it's been submitted but not included in a block yet. Then, we include the transaction in block 2, after the EMA has rolled over. When the EMA rolls over, we will trigger a failure if the promoted transaction’s price is checked. This approach allows us to pinpoint any price inconsistencies accurately. Think of it like a time-lapse, where we can see if the price changes as the transaction moves through the system.

Test Breakdown: The Step-by-Step Approach

Let's break down the test step by step. First, we need to create a test case that replicates the scenario we're trying to validate. This test case includes a 'promoted transaction,' which is submitted. Then, it undergoes a price check that must return the correct, initial price. Next, this transaction will be included in the block 2. After including the transaction, the EMA is triggered to recalculate. After the EMA recalculates, we perform another price check. The test should fail if the price check after inclusion and the EMA recalculation doesn't match the initial price. The whole test workflow should be automated, and the test should integrate seamlessly with our existing testing framework.

Here’s a more detailed breakdown:

1. Setup the Environment: Initialize the test environment, configure the EMA interval to two blocks, and set up the necessary accounts and transaction data. This step prepares the canvas for the main event.
2. Submit the Transaction: Submit a transaction for inclusion in a block. This transaction will be marked as a 'JUST submit,' meaning it is submitted but not yet included in a block.
3. Initial Price Check: Verify the transaction’s price before it's included in any block. This initial check establishes a baseline.
4. Block 2 Inclusion & EMA Roll Over: Include the transaction in block 2. This step triggers the EMA's recalculation process.
5. Final Price Check: After inclusion and the EMA recalculation, perform a second price check. This check verifies whether the transaction price has remained consistent.
6. Assertion and Failure: The test should assert that the final price check matches the initial price check. Any discrepancy should result in the test failing.

This methodical approach ensures that we can accurately identify any inconsistencies in the transaction price. If the test fails, it indicates that something went wrong during the price verification process, which in turn alerts us to potential security or performance issues.

Code Implementation and Integration

Now, let's talk about the nitty-gritty: the code. The test should be written in a manner that’s easy to read, maintain, and integrate into our existing testing framework. Here's a brief guideline:

1. Framework Compatibility: Ensure the test is compatible with our testing framework. This usually involves writing the test within the framework's structure, so that it can be easily run and managed.
2. Test Case Setup: Define a clear test case that specifies the scenario, input data, and expected outcomes. The setup should be straightforward, so that it's easy to understand and replicate the test.
3. Transaction Submission: The code should submit the transaction programmatically, using our API or any relevant functions. Make sure to log the transaction hash and other relevant details.
4. Price Check Implementation: Implement the price checks. This will involve calling the price check function at different points in the test and comparing the results.
5. Assertion Logic: Implement clear assertion logic that checks whether the prices match. If the prices do not match, the test should fail immediately, and provide helpful error messages.
6. Cleanup: Make sure that after the test is over, it cleans up all resources that it used, such as accounts or temporary files.

The main idea is to make the test self-contained and easy to run. The goal is to provide reliable and accurate results when we run it. We aim for the code to be clean, so that other developers can understand the test and make sure that this test functions correctly.

Expected Results and Troubleshooting

The expected result of the test is that it should pass if the price remains consistent. If the test fails, that means we found something that is wrong with price checks. When the test fails, there are a few things to check:

• Verify EMA Configuration: Double-check the EMA configuration to ensure it is set up correctly.
• Price Calculation: Review how prices are calculated to identify any calculation errors.
• Transaction Processing: Look at the transaction processing workflow. Make sure it processes the prices correctly.

Additionally, it's really important to keep detailed logs. These logs should include the transaction hash, timestamps, and the prices obtained from each check. Detailed logs will make it a lot easier to trace the origin of the problem and solve it.

Conclusion: Keeping it Secure and Reliable

Creating this regression test is super crucial for maintaining the security and reliability of our transaction processing system. By rigorously checking the price consistency of promoted transactions, we make sure that our users can trust that prices won't mysteriously change. This, in turn, helps prevent potential exploits and keeps the platform running smoothly. As a team, we want to deliver a dependable and consistent experience to our users. Our regression test is a vital step in this process. So, let’s get this test implemented, and ensure that our platform is as robust and trustworthy as can be. This test is a cornerstone for the future of our platform, ensuring we provide our users with a reliable and predictable environment. Thanks for taking the time to read this, and let's go build something awesome!